Journal of Biogeography. 2021;00:1–14.
Received: 17 June 2020
Revised: 28 December 2020
Accepted: 11 January 2021
The relationship between niche breadth and range size of
beech (Fagus) species worldwide
Qiong Cai1,2 | Erik Welk2,3 | Chengjun Ji1 | Wenjing Fang1 |
Francesco M. Sabatini3,2 | Jianxiao Zhu1 | Jiangling Zhu1 | Zhiyao Tang1 |
Fabio Attorre4 | Juan A. Campos5 | Andraž Čarni6,7 | Milan Chytrý8 |
Süleyman Çoban9 | Jürgen Dengler3,10,11 | Jiri Dolezal12,13 | Richard Field14 |
József P. Frink15 | Hamid Gholizadeh16 | Adrian Indreica17 | Ute Jandt2,3 |
Dirk N. Karger18 | Jonathan Lenoir19 | Robert K. Peet20 | Remigiusz Pielech21 |
Michele De Sanctis4 | Franziska Schrodt14 | Jens- Christian Svenning22,23 |
Cindy Q. Tang24 | Ioannis Tsiripidis25 | Wolfgang Willner26 | Kubota Yasuhiro27 |
Jingyun Fang1 | Helge Bruelheide2,3
1Department of Ecology, College of Urban and Environmental Sciences, and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking
University, Beijing, China
2Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle- Wittenberg, Halle, Germany
3German Centre for Integrative Biodiversity Research (iDiv) Halle- Jena- Leipzig, Leipzig, Germany
4Department of Environmental Biology, University Sapienza of Rome, Rome, Italy
5Department of Plant Biology and Ecolog y, University of the Basque Country UPV/EHU, Bilbao, Spain
6Research Centre of the Slovenian Academy of Sciences and Arts, Institute of Biology, Ljubljana, Slovenia
7University of Nova Gorica, Nova Gorica, Slovenia
8Department of Botany and Zoology, Faculty of Science, Masaryk University, Brno, Czech Republic
9Department of Silviculture, Faculty of Forestry, Istanbul University- Cerrahpasa, Sarıyer, Istanbul, Turkey
10Vegetation Ecolog y, Institute of Natural Resource Management (IUNR), Zurich University of Applied Sciences (ZHAW), Wädenswil, Switzerland
11Plant Ecology, Bayreuth Centre of Ecology and Environmental Research (BayCEER), University of Bayreuth, Germany
12Institute of Botany, The Czech Academy of Sciences, Průhonice, Czech Republic
13Depar tment of Botany, Facult y of Science, Universit y of South Bohemia, České Budějovice, Czech Republic
14School of Geography, University of Nottingham, Nottingham, UK
15National Institute for Research and Development in Forestry “Marin Drăcea”, Cluj- Napoca, Romania
16Depar tment of Biology, Faculty of Basic Sciences, University of Mazandaran, Babolsar, Iran
17Depar tment of Silviculture, Transilvania University of Brasov, Brasov, Romania
18Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
19UR « Ecologie et Dynamique des Systèmes Anthropisés » (EDYSAN, UMR 7058 CNRS), Université de Picardie Jules Verne, Amiens, France
20Depar tment of Biolog y, University of Nor th Carolina, Chapel Hill, NC , USA
21Department of Forest Biodiversity, Universit y of Agriculture, Kraków, Poland
22Centre for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Biology, Aarhus University, Aarhus C , Denmark
23Section for Ecoinformatics and Biodiversity, Department of Biology, Aarhus University, Aarhus C, Denmark
24Institute of Ecology and Geobotany, College of Ecolog y and Environmental Science, Yunnan University, Kunming, Yunnan, China
25Department of Botany, School of Biology, Aristotle University of Thessaloniki, Thessaloniki, Greece
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium,
provided the original work is properly cited.
© 2021 The Authors. Journal of Biogeography published by John Wiley & Sons Ltd.
Handli ng editor: Enri que Marítnez- Meyer
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26Depar tment of Botany and Biodiversity
Research, University of Vienna, Wien,
27Faculty of Science, University of the
Ryukyus, Nishihara, Okinawa, Japan
Helge Bruelheide, Institute of Biology/
Geobot any and Botanical Garden, Martin
Luther University Halle- Wittenberg, Am
Kirchtor 1, 06108 Halle, Germany.
National Natural Science Foundation of
China; Ministry of Science and Technology
of China; National Key Research and
Development Program of China; Grantová
Agentura České Republiky; Chinese
Scholarship Council; Independent
Research Fund Denmark; Natural Sciences
project TREECHANGE; Villum Fonden;
German Research Foundation; Ministry of
Education, Youth and Sport of the Czech
Republic, program Inter- Excellence
Aim: This work explores whether the commonly observed positive range size– niche
breadth relationship exists for Fagus, one of the most dominant and widespread broad-
leaved deciduous tree genera in temperate forests of the Northern Hemisphere.
Additionally, we ask whether the 10 extant Fagus species’ niche breadths and climatic
tolerances are under phylogenetic control.
Location: Northern Hemisphere temperate forests.
Tax o n: Fagus L.
Methods: Combining the global vegetation database sPlot with Chinese vegetation
data, we extracted 107,758 relevés containing Fagus species. We estimated biotic
and climatic niche breadths per species using plot- based co- occurrence data and a
resource- based approach, respectively. We examined the relationships of these
estimates with range size and tested for their phylogenetic signal, prior to which a
Random Forest (RF) analysis was applied to test which climatic properties are most
conserved across the Fagus species.
Results: Neither biotic niche breadth nor climatic niche breadth was correlated with
range size, and the two niche breadths were incongruent as well. Notably, the wide-
spread North American F. grandifolia had a distinctly smaller biotic niche breadth than
the Chinese Fagus species (F. engleriana, F. hayatae, F. longipetiolata and F. lucida) with
restricted distributions in isolated mountains. The RF analysis revealed that cold toler-
ance did not differ among the 10 species, and thus may represent an ancestral, fixed
trait. In addition, neither biotic nor climatic niche breadths are under phylogenetic
Main Conclusions: We interpret the lack of a general positive range size– niche
breadth relationship within the genus Fagus as a result of the widespread distribu-
tion, high among- region variation in available niche space, landscape heterogeneity
and Quaternary history. The results hold when estimating niche sizes either by fine-
scale co- occurrence data or coarse- scale climate data, suggesting a mechanistic link
between factors operating across spatial scales. Besides, there was no evidence for
diverging ecological specialization within the genus Fagus.
climatic niche, co- occurrence data, deciduous species, Fagus, geographical range size, niche
breadth, niche evolution, phylogenetic signal, temperate forest flora, vegetation- plot data
1 | INTRODUCTION
Geographical range size is generally defined as the 2- dimensional
extent of the spatial distribution of a species based on latitudinal
and longitudinal extents (Gaston, 1991), whereas a species’ real-
ized niche is widely understood as the n- dimensional hypervol-
ume (Hutchinson, 1957) defined by the multi- dimensional range
of abiotic and biotic conditions under which it can sustain natural
populations (Blonder, 2018). The quantification and comparison
of niche hypervolumes (hereafter niche breadth) have long been
of interest to ecologists (e.g. Blonder et al., 2014; Fridley et al.,
2007; Hutchinson, 1957; Junker et al., 2016; Kambach et al., 2019;
Sexton et al., 2017; Smith, 1982). Properties like species’ niche
breadths and niche overlaps are proposed to affect co- occurrence
patterns at the community level (Bar- Massada, 2015), and realized
niche breadths are of ten used to def ine the degree of species spe-
cialization (Devictor et al., 2010). Since specialists (species with a
narrow niche) are thought to be more vulnerable to current and
future climate change than generalists (Devictor et al., 2010; but
see Colles et al., 2009), determining species’ niche breadth can
help identify priority species for conser vation ac tions (Boulangeat
et al., 2012).
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A positive relationship between range size and niche breadth
has been proposed by the “niche breadth hypothesis” (Sheth et al.,
2020). A wid e niche allows a spe cies to cop e with a wi de range of en-
vironmental conditions (Brown, 1984). Mechanistically, a wide niche
breadth can be brought about either by generalistic genotypes or
by many different particularly adapted genotypes that replace each
other in different parts of the geographical range (i.e. geographical
vicariants) (Sheth et al., 2020). Both mechanisms would be reflected
in a larger distribution range. Most studies have confirmed such a
positive correlation (Boulangeat et al., 2012; Brown, 1984; Kambach
et al., 2019; Slatyer et al., 2013; Sporbert et al., 2019; Zelený &
Chytrý, 2019). For example, in a study on about 1200 plant species in
the French Alps, specialist species were found to be more geograph-
ically restricted than generalist species (Boulangeat et al., 2012). The
same pattern was found in the Czech flora (Zelený & Chytrý, 2019).
Similarly, Kambach et al. (2019) reported a positive relationship be-
tween niche breadth and geographical range size, both regionally
(1255 plant species in the European Alps) and globally (180 plant
species). Recently, a meta- analysis of 64 studies worldwide, found
widespread convergence between geographical range size and niche
breadth, even after taking into account differences in niche breadth
measurements, taxonomic groups, spatial scales and sampling ef-
fects across studies (Slatyer et al., 2013). This has raised concerns
for specialist species that might be disproportionally affected by
habitat loss (Staude et al., 2020). However, contrasting patterns have
also been observed (Kambach et al., 2019; Slatyer et al., 2013), po-
tentially reflecting the multitude of factors affecting range size and
realized niche breadth, such as dispersal abilities, regional availability
of suitable niche space and historical events.
One reason why the positive niche breadth– range size relation-
ship is not systematically observed in nature might stem from the
many ways niche sizes are calculated. Numerous approaches have
been proposed to estimate the realized niche breadth of species
(Guisan & Zimmermann, 2000; Sexton et al., 2017). The resource-
based method (Smith, 1982) determines niche breadth as the range
of favourable conditions along certain environmental gradients,
such as temperature, soil moisture and nutrients, and light avail-
ability. It estimates the Grinnellian niche (Grinnell, 1917; Grinnell &
Swarth, 1913) and it is the most widely applied method. However, as
the resulting niche breadth depends on the selection of niche axes,
it will only represent a part of the whole multi- dimensional niche as
defined by Hutchinson (Devictor et al., 2010).
As large distribution ranges involve a higher probability to in-
clude a higher variation in climatic conditions, a positive relationship
between range size and climatic niche breadth would not be sur-
prising (Slatyer et al., 2013). However, it is much less clear whether
range size, as a global distribution characteristic, can be predicted
from niche breadth estimates derived from the local scale of popula-
tions and the communities in which the populations occur (Kambach
et al., 2019). Here, we focus on the community approach, which
relies on the assumption that local- scale environmental conditions
are reflected in community composition. At this scale, local inter-
actions between species come into play, which can either reinforce
broad- scale climatically induced patterns or blur them (Sheth et al.,
2020). In the first case, a wider range of communities in which a
species occurs would not only indicate the existence of higher en-
vironmental variation within the species’ range, but also provide
evidence that the species is able to compete with many other co-
occurring species under these conditions. Thus, in this case the niche
breadth– range size relationship would become clearer because en-
vironmentally unsuitable habitats within the species’ range would
remain unconsidered. Alternatively, local interactions might weaken
the niche brea dth– range size relationship, as the presence and abun-
dance of the co- resident species might depend on different site fac-
tors than those relevant for the species under consideration.
One method to estimate this niche breadth based on commu-
nity composition uses community turnover rates across plots (the
taxonomic β- diversity) as a measure of species’ niche breadth
(Fridley et al., 2007; successively modified by Zelený, 2009 and
Manthey & Fridley, 2009). The fundamental assumption of the co-
occurrence- based (biotic) niche concept is that widespread species
are generalists that should occur with a broader range of commu-
nity compositions (i.e. in a higher number of different communities)
compared to specialists, given an equal drawn number of plots in
which the species occurs (Fridley et al., 2007). Overall, this method
characterizes both the Grinnellian niche and the Eltonian niche
(Elton, 1927), as it quantifies species’ response to multi- dimensional
environment gradients and considers species interactions as well
(Devictor et al., 2010; Fridley et al., 2007). In addition, it can be
applied where environmental information is unavailable. Resource-
based and co- occurrence- based approaches differ in the dimensions
measured and spatial scales, and can serve as complementary meth-
ods to estimate species’ niches. While results based on the two ap-
proaches are not necessarily correlated (Emery et al., 2012; Pannek
et al., 2016), a positive correlation is expected at broad spatial scales
(Kambach et al., 2019).
Fagus is a key genus of the northern temperate forest flora.
While phylogenetic relationships (e.g. Denk, 2003; Renner et al.,
2016; Shen, 1992), climatic limits (Fang & Lechowicz, 2006), biogeo-
graphical history (Denk & Grimm, 2009) and community composi-
tion (e.g. Hukusima et al., 2013; Kavgaci et al., 2012; Willner et al.,
2017) within the genus have been extensively studied, much less
attention has been given to the range size and niche properties of
the component species. This knowledge is valuable as it may help
understand how Fagus species might respond to climate change.
Increasing temperatures and more frequent extreme events, such as
repeated heatwaves and summer droughts, have been projected for
many mid- latitude regions (Booth et al., 2012; Geßler et al., 2007).
Fagus species such as F. sylvatica and F. grandifolia are sensitive to
high temperature and repeated drought events (Booth et al., 2012;
Clark et al., 2011; Silva et al., 2012), and the distribution of European
beech (F. sylvatica) has been projected to shift northward in a fu-
ture climate (Kramer et al., 2010). Studying the relationship between
range size and niche breadth could provide valuable information
for predicting the future distribution of Fagus species (Sheth et al.,
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Species’ responses to past environment changes could have
been influenced dramatically by evolutionary processes (Kramer
et al., 2010; Parmesan, 2006). Species differ in their environmen-
tal niche space because their ancestor populations were adapted
to different conditions within the ancestral range, or the an-
cestor was sufficiently plastic to cope with different conditions
(Bromham et al., 2020). In the course of speciation, we would ex-
pect that the descendant species share either a similar adaptation
to local environment or the generalistic genotypic constitution
with their ancestors. In both cases, the niche characteristics of
closely related species should be more similar than those of more
distantly related species (Losos, 2008). Consequently, it is im-
portant to analyse niche properties in a phylogenetic framework
(Graham et al., 2004; Kozak & Wiens, 2010). Information as to
which niche characteristics are more strongly affected by phylo-
genetic control might help establish hypotheses on the underlying
mechanisms responsible for range dynamics and speciation and
provide insights into the evolution of different niche axes (Emery
et al., 2012; Evans et al., 2009). Variation among different Fagus
species may be expected because of regionally varying palaeocli-
matic forces on range dynamics (Dynesius & Jansson, 200 0; Magri
et al., 2006). In the genus Fagus, the widespread and dominant
North American F. grandifolia belongs to a more ancestral clade
compared to the non- dominant, regionally rare and small- ranged
Chinese species (Oh et al., 2016; but see Renner et al., 2016 and
Jiang et al ., 20 20). This phylo ge net ic pa tte rn co uld suggest an evo-
lutionary tendency towards ecological specialization.
As mentioned above, because species with larger ecological
niches occur in a broader range of habitats, they tend to have
larger distribution ranges and total population sizes. These condi-
tions should provide higher chances for speciation events in quan-
titative and qualitative terms. A broader habitat range provides a
higher probability for local adaptation processes. Such ecotypes
have the chance to get isolated from the main population by eco-
logical or spatial vicariance. The quantitative difference to small-
ranged species provides a stochastically higher chance for such
events as well as for long- distance dispersal events. This opens
another possibility for speciation processes due to geographical
isolation. Testing whether interspecific similarities of niche char-
acteristics and phylogenetic relatedness are positively correlated
(Blomberg et al., 2003; Losos, 2008; Wiens et al., 2010), could
provide hints for evolutionary tendencies towards ecological
specialization. In addition, identifying the key climatic factors for
evolution and speciation of the Fagus species might also enhance
our understanding on their response to climate change. So far,
although several studies have explored the roles of climatic (e.g,
Evans et al., 2009; Graham et al., 2004; Kozak & Weins, 2006) or
habitat niche evolution (e.g., Emery et al., 2012) in speciation, this
approach has rarely been applied to species’ co- occurrence- based
assessment of niche breadth.
During the last decades, extensive species co- occurrence
data have been accumulated for forest stands in which the
genus Fagus occurs. Combining sPlot— the global vegetation plot
database (Bruelheide et al., 2019)— with an unpublished Chinese
vegetation database, we extracted 107,758 relevés in which at
least one Fagus sp ecies occurs . Using this unique dataset and th e
distribution data from Chorology Database Halle (http://choro
logie.biolo gie.uni- halle.de//areal e/), we estimated the range size
and niche breadth of all extant Fagus species, and explored the
relationship between them. Accordingly, we tested the following
hypotheses: (H1) The commonly found positive relationship be-
tween range size and niche breadth applies to the genus Fagus;
(H2) biotic and climatic niche breadths are correlated; and (H3)
the Fagus species’ niche similarities are positively correlated
wit h phylogenetic relatedn ess. Although H1 is a general assump-
tion in species distribution modelling, it has rarely been tested
with different approaches to niche breadth estimation; doing so
for all species of a key genus of northern temperate forests is,
therefore, particularly valuable. Confirming H2 would demon-
strate that fine- scale determinants of biotic niche breadth are
transferable to the broad- scale characteristics represented by
climatic niche breadth. Finally, the results on H3 would shed light
on the evolution of Fagus species’ niche properties, and thus
improve our ability to model potential future changes of Fagus
2 | MATERIALS AND METHODS
2.1 | Study species
The genus Fagus includes widespread as well as relatively rare spe-
cies distributed across the Northern Hemisphere, from eastern
North America, Europe and western Asia to eastern Asia (Figure 1).
There are four Fagus species in China (F. engleriana, F. hayatae, F.
longipetiolata, F. lucida), with F. longipetiolata distributed in north-
ern Vietnam and F. hayatae in Taiwan Island. Two species occur in
Japan (F. crenata, F. japonica) and one on Ulleungdo Island in South
Korea (F. multinervis) (Fang & Lechowicz, 2006; Oh et al., 2016).
European beech (F. sylvatica) occurs in Europe, and F. orientalis in
western Asia and southeast Europe (Willner et al., 2017). Fagus
grandifolia is distributed in eastern North America, with F. grandi-
folia subsp. mexicana having a narrow, isolated range in the moun-
tains of Mexico. It is noteworthy that the taxonomic status of the
three geographically- isolated segregates (F. multinervis, F. orientalis
and F. grandifolia subsp. mexicana) has been debated for a long time.
In some studies, F. multinervis and F. orientalis have been treated as
subspecies (Renner et al., 2016), while there are recent phylogenetic
hypotheses that recognize F. grandifolia subsp. mexicana as a distinct
species (Jiang et al., 2020).
2.2 | Datasets for niche breadth estimation
The data used were mainly obtained from sPlot— the global
vegetation- plot database— which has a worldwide coverage
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and a standardized taxonomic nomenclature (Bruelheide et al.,
2019). As data for Fagus in China were quite limited in sPlot, 219
additional Fagus plot data from China were added from our own
unpublished field records. The taxonomic backbone of sPlot was
used to harmonize the species nomenclature of these additional
records. Species co- occurrences in the tree, shrub and herba-
ceous layer of each vegetation plot were used for co- occurrence-
related analyses. Additionally, the spatial coordinates (latitude
and longitude) of the plots were used to extract climatic attrib-
utes. As we were interested in estimating niche breadth from
the full range of biotic constellations, we did not apply any mini-
mum threshold for the cover of Fagus species in the plot records.
Altogether, 107,758 vegetation plots in which at least one Fagus
tree species occurs were obtained for the analyses (Figure S1,
2.3 | Datasets for range size estimation
The geographical distribution of the 10 Fagus species (Figure 1) was
based not only on the occurrence records described above but also on
the data collected by the Chorology Working Group at the University
of Halle- Wittenberg, Germany (Chorology Database Halle, CDH; http://
choro logie.biolo gie.uni- halle.de//areal e/), which has compiled a wide
range of data sources. For example, distribution data of the Chinese
Fagus species were primarily collected from ‘Atlas of woody plants in
China: distribution and climate’ (Fang et al., 2011). The data included pol-
ygon and point features. For methodological details, see Caudullo et al.
(2017). For each Fagus species, the range size was calculated as the
geographical area (km2) of the range polygons in an equal- area carto-
graphic projection (Lambert azimuthal equal- area projection). Isolated
point clusters were converted to minimum convex polygons (MCPs).
FIGURE 1 Range maps of the 10
extant Fagus species worldwide. The
colour spectrum reflects the phylogenetic
relationships of the 10 species (see Figure
5). (a) Global distribution of Fagus and
detail enlargement for (b) North America;
(c) Europe and West Asia; (d) East
Asia; and (e) Ulleungdo Island in South
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2.4 | Climate data
For the localities of all 107,758 selected plots, we extracted raster
cell values from grid layers of the 19 bioclimatic variables (BIO01
to BIO19) provided by the CHELSA database (https://chels a- clima
te.org/; Karger et al., 2017). The spatial resolution was 30 arc seconds,
corresponding to about 0.64 km × 0.93 km = 0.6 km2 at the average
latitude of the plots (46.31°N). For those plots along the coastlines
resulting to be located in the sea due to coarse location accuracy, we
extracted the climate information of the closest terrestrial grid cells
with the recorded elevation using the snap function in ArcGIS.
2.5 | Estimation of biotic (co- occurrence- based)
niches from plot data
To estimate co- occurrence- based niche breadth, we generally fol-
lowed the approach proposed by Fridley et al. (2007), which uses
the taxonomic β- diversity metric among the set of plant communi-
ties (here, vegetation plots) in which a focal plant species occurs.
To measure plot dissimilarity, we chose the multiple Simpson index
(Baselga et al., 2007), which can disentangle changes in species
composition caused by changes in species identities (species turno-
ver) from those caused by species richness differences (nestedness
effect), whilst being independent of the absolute species richness
in the plots (Baselga et al., 2007; Manthey & Fridley, 2009). As
the quantities of plots varied a lot among different Fagus species
(Table 1), we conducted a resampling procedure to control for pos-
sible sample size effects. For each of the 10 Fagus species we calcu-
lated niche breadth 100 times by randomly drawing 20 plots with
replacement out of the total number of plots that contain the focal
species, and then taking the average dissimilarity value of the 100
iterations (Fridley et al., 2007; Pannek et al., 2016). We then calcu-
lated the variance of the dissimilarity values across the 100 runs.
Results based on other dissimilarity indices for turnover calculations,
i.e. the Jaccard and Sørensen index (Manthey & Fridley, 2009), are
presented in the Supporting Information (Figure S2). The Sørensen
index is a linear function of the multiplicative Whittaker's β- diversity
metric (βw), which eliminates possible effects of species pool sizes
(Manthey & Fridley, 2009; Zelený, 2009).
2.6 | Estimation of climatic niches from plot data
We applied the method of dynamic range boxes (DRB) to estimate the
climatic niche breadth since it has proven to be relatively robust to
sampling effects and outliers, especially at high dimensionality (Junker
et al., 2016). Accordingly, we calculated the realized climatic niche
breadth based on the above- mentioned bioclimatic variables, using
the R package ‘dynRB’ (Schreyer et al., 2018). To avoid bias related
to inter- correlation, we excluded one of those variables with abso-
lute pairwise correlation r > 0.75 and we thereby limited our selec-
tion to 10 variables as follows: BIO02 (Mean Diurnal Range); BIO03
(Isothermality); BIO05 (Max Temperature of Warmest Month); BIO06
(Min Temperature of Coldest Month); BIO07 (Temperature Annual
Range); BIO08 (Mean Temperature of Wettest Quarter); BIO09 (Mean
Temperature of Driest Quarter); BIO13 (Precipitation of Wettest
Month); BIO15 (Precipitation Seasonality); and BIO17 (Precipitation
of Driest Quarter). Original dimensions of the climatic variables were
replaced with the first five principal components of a principal com-
ponent analysis (PCA) (accounting for 91.8% of the variation) to avoid
possible interdependence of predictors (Junker et al., 2016).
To limit pseudo- replication at a given site, in cases where two
or more plots had identical spatial coordinates, only one plot was
F. crenata 4811 1.6 × 10531.5– 42.7 130.1°E– 142.1°E
F. engleriana 71 2.6 × 1053 0 . 1 – 3 3 . 8 103.6°E– 118 .8°E
F. grandifolia 3 574 2.1 × 10619.6 – 4 6.1 68.2°W– 97.0°W
F. ha yatae 50 3.6 × 10424.5– 33.5 102.4°E– 121.8°E
F. japonica 1187 8.0 × 10432.4– 40.0 131°E– 141.9°E
F. longipetiolata 58 7.5 × 10522.9– 32.9 102.4°E– 120.7°E
F. lucida 90 4.4 × 10524.9– 32. 6 103.9°E– 119.7°E
F. multinervis 35 3.7 × 1013 7.49 – 3 7. 5 3 130.8°E– 130.9°E
F. orientalis 1316 1.7 × 10536.0– 50.4 21.5°E– 53.1°E
F. sylvatica 97, 0 4 5 1.3 × 10637. 7– 57. 5 5.3°W– 28.3°E
aThere are some plots with more than one Fagus species. Therefore, the sum of plot numbers in the
table is greater than the total number of plots, which is 107,758.
bFor F. grandifolia, the geographical range of plots excluding those in Mexico (19.6– 19.7°N and
96.9– 97.0°W) is 30.4– 46.1°N and 68.2– 94.3°W. For F. h ayatae, the geographical range of plots
in mainland China is 28.6– 33.5°N and 102.4– 120.7°E, and that of plots on Taiwan Island is
24.5– 24.7°N and 121.3– 121.8°E.
TAB LE 1 Geographical range sizes and
plot information of the 10 extant Fagus
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selected randomly. As a result, the sample size for the climatic niche
estimation was reduced to 61,717 plots. We used two different ag-
gregation functions (‘mean’ and ‘gmean’, both included in the pack-
age ‘dynRB’) to compare the coordinate- wise volumes. Note that the
‘product’ method was omitted as it was not recommended by the
authors (Junker et al., 2016). Results based on the ‘mean’ method are
shown in the Supporting Information (Figure S3).
2.7 | Phylogenetic analysis
Before using phylogenetic methods to test whether specific mac-
roclimatic traits are species- specific across genera, we ran a
Random Forest (RF) analysis to select the key bioclimatic variables.
Specifically, we quantified the discriminability of each bioclimatic
variable range between the sister species. We employed two widely
used variable importance measures: the mean decrease accuracy
and mean decrease Gini index (Breiman, 2001). Only the plot data
with distinct coordinates (n = 61,717) were used here.
We calculated RF ensembles of recursive classification trees with
the ‘randomForest’ package in R (Breiman, 2002). As settings, we
used 10,000 iterations and the ‘tuneRF’ function to identify the ‘opti-
mal’ number of input variables randomly chosen at each node. Since
the number of plots per Fagus species varied considerably (n = 11 to
54,397), both a fixed sample size (n = 10) approach and a proportion-
ate stratified sampling procedure (following the species sequence in
Table 1, n = 3690; 40; 1840; 40; 1030; 50; 60; 10; 270; and 16,300,
respectively, with replacement) were adopted. For comparison, a con-
servative variant with the fixed sample size of n = 10 was calculated.
Out- of- bag (OOB) estimation of error rate was used to assess clas-
sification success and a permutation cross- validation test with 20%
withhold test data was used to control for overfitting.
To assess whether niche breadth estimates as well as the least
and most discriminating bioclimatic variables identified by the RF
analysis (taking the 5th and 95th percentiles, respectively) are under
phylogenetic control or show a random pattern of evolution, phy-
logenetic signals were tested across all 10 Fagus species. For each
species, we calculated the biotic and climatic niche breadth esti-
mates and the distinctive bioclimatic variables. Blomberg's K value
is an indicator of the strength of the phylogenetic signal, which in-
dicates strong phylogenetic control of characteristics when greater
than one, and a random pattern of evolution when close to zero
(Blomberg et al., 2003; Kembel, 2010). Blomberg's K values were
calculated based on the phylogenetic trees as provided in Qian and
Jin (2016) and Oh et al. (2016).
2.8 | Statistical analyses
We tested for differences in biotic niche breadth between the 10
Fagus species with a one- way analysis of variance (ANOVA) and
Tukey's HSD post hoc tests, using an n = 100 random selection of
plot records as replicates. To test hypothesis H1 (i.e. that range size
is related to niche breadth) and H2 (i.e. that biotic and climatic niche
breadths are correlated), we assessed the relationships between the
different niche traits and range size by performing the phylogeneti-
cally corrected generalized least- squares (PGLS) regression using the
R package ‘caper’ (Orme et al., 2018). Considering the relatively small
sample sizes and the outlier species F. multinervis, we further assessed
the relationships with a Spearman's correlation test. In addition, the
PGLS regression and Spearman's correlation test were also performed
when excluding F. multinervis. For hypothesis H3, which proposes that
biotic and climatic niche breadths are non- randomly associated with
phylogeny, we calculated the phylogenetic signal, using the ‘picante’
package in R (Kembel, 2010). Plotting of the phylogenetic signals
was done with ‘phylo4d’ from the ‘phytools’ package (Revell & Revell,
2019). The RF analysis was done using the ‘rf’, ‘rfUtilities’, and ‘ran-
domForestExplainer’ packages. All statistical analyses were conducted
with R v3.5.1 (R Core Team, 2018), and further graphs were produced
with the R package ‘ggplot2’ and ArcGIS 10.3.
3 | RESULTS
3.1 | Overall patterns of range sizes and niche
Geographical range sizes of the 10 Fagus species differed by five orders
of magnitude, ranging from 37 km2 (F. multinervis) to 2.1 × 106 km2 (F.
grandifolia) (Table 1). Out of the four Chinese Fagus species (F. longipet-
iolata, F. lucida, F. engleriana and F. hayatae), F. hayatae had the smallest
range size (3.6 × 104 km2), but also a wide disjunction between the pop-
ulations of mainland China and Taiwan. The ranges of the other three
Chinese species were intermediate in size, but all were much smaller
than those of F. grandifolia and F. sylvatica (1.3 × 106 km2). Fagus ori-
entalis (1.7 × 105 km2) and the two Japanese Fagus species had larger,
but still relatively small range sizes (8.0 × 104 and 1.6 × 105 km2 for
F. japonica and F. crenata, respectively) (Table 1). Despite some minor
incongruences among different estimation methods, results obtained
from the three co- occurrence approaches based on plot data were
largely aligned, and so were the two climatic niche metrics calculated
with different aggregation methods (Figures 2, 4g, S2, S3). Regarding
the co- occurrence- based metric of niche breadth (multiple Simpson
index), the Chinese Fagus species displayed the broadest biotic niches,
while the Fagus species in Europe and West Asia had intermediate
ones, and those in North America, Japan and Korea had relatively nar-
row niches (Figure 2). Similar patterns were observed based on the
Jaccard and Sørensen index (Figure S2). In terms of climatic niche
breadth, the Chinese species F. hayatae displayed the largest climatic
niche breadth, followed by the West Asian and European Fagus spe-
cies (F. orientalis and F. sylvatica). The North American and Japanese
Fagus species had intermediate climatic niches, while the Korean spe-
cies F. multinervis had the narrowest one (Figure 3). The aggregation
method ‘mean’ resulted in a similar pattern (Figure S3). A PCA of the
10 climatic variables also showed that plots of F. hayatae had a wide
range along the first two axes (Figure S4).
CAI et A l.
3.2 | Relationships between range sizes and
According to the PGLS regression and Spearman's correlation test,
neither the biotic nor the climatic niche breadth estimate was related
to range size (p > 0.05; Figure 4a– b, g). Although log- transformed
range size exhibited a positive relationship with both biotic and
climatic niche breadth (R2 ranging from 0.57 to 0.87, p ≤ 0.01;
Figure 4c– d), these relationships were strongly determined by the
influential point of F. multinervis. When excluding F. multinervis, the
relationships were not significant any more (p > 0.05; Figure 4c– d).
The biotic niche breadth estimates were significantly correlated
with the climatic niche breadth values based on PGLS regression
(R2 ranging from 0.43 to 0.72, p < 0.05; Figure 4e– f). However,
these relationships were also strongly influenced by F. multinervis
(Figure 4e– f). Both PGLS regression excluding F. multinervis and the
Spearman's correlation test (Figure 4g) exhibited no significant rela-
tionships between the two niche breadth measures (p > 0.05).
3.3 | Phylogenetic analyses of climatic
tolerances and niche properties
The RF analysis successfully classified the species by climate with an
out- of- bag (OOB) error rate of 11.1% when using a fixed sample size
(n = 10), but reaching an OOB error rate of 1.95% when using pro-
portional sample sizes. Similar values were obtained with the cross-
validation approach when withholding 20% test datasets (9.86% and
2.03%, respectively). For both sampling strategies, the bioclimatic
variable BIO03 (Isothermality, which is the mean diurnal range of
temperature divided by the annual range of temperature, i.e. BIO02/
BIO07) had the strongest importance for discriminating the species,
as it returned the largest decrease in accuracy and increase in Gini
node impurity when excluded (Figure S5). In contrast, the exclusion
of the bioclimatic variable BIO06 (Minimum temperature of the
coldest month) had the lowest importance (Figure S5).
Blomberg's K values were smaller than one for all the biotic and
climatic niche characteristics as well as the two aforementioned
bioclimatic variables (BIO03 and BIO06). No biotic or climatic niche
characteristics were significantly different from a random distri-
bution (p > 0.1; Figure 5), suggesting that we cannot conclude that
these characteristics are phylogenetically conserved within the
genus Fagus. Rather, small and large niche breadths are distributed
randomly among the clades within Fagus.
4 | DISCUSSION
Contrary to our first hypothesis and the commonly reported posi-
tive relationship between range size and niche breadth (Boulangeat
FIGURE 2 Co- occurrence- based niche
breadths of the 10 extant Fagus species
using multiple Simpson index for turnover
calculations. The colour spectrum follows
the distribution range maps (Figure 1).
Different letters indicate significant
differences according to a Tukey's HSD
post- hoc test (p < 0.05)
FIGURE 3 Climatic niche breadths of
the 10 extant Fagus species based on the
resource- based method of dynamic range
boxes (DRB). The aggregation method
used was ‘gmean’ (Junker et al., 2016). The
colour spectrum follows the distribution
range maps (Figure 1)
CAI et A l.
et al., 2012; Brown, 1984; Kambach et al., 2019; Sheth et al.,
2020; Slatyer et al., 2013), we found no significant relationship
between range size and the biotic and climatic niche breadth es-
timates for the species in the globally important tree genus Fagus.
Setting possible methodological issues aside (see Appendix 1 in the
Supporting Information), there are many biological, geographical and
historical factors that might affect the niche breadth– range size re-
lationship for these closely related species, such as dispersal ability
FIGURE 4 Relationships between
different niche breadths and range size
(a– b) or log- transformed range size (c– d),
and between biotic and climatic niche
breadth (e– f). Panels a– f are based on the
phylogenetically corrected generalized
least- squares (PGLS) regression and panel
g is based on the Spearman's correlation
test (p < 0.05). Considering the outlier
point of Fagus multinervis, fitted lines
and coefficients of the PGLS regression
of the 10 Fagus species are not shown
in panels c– f. Multiple Simpson, Jaccard
and Sørensen are different indices for
biotic niche estimation. Mean and gmean
represent different aggregation methods
for climatic niche estimation and refer
to the arithmetic and the geometric
mean of the different niche dimensions,
respectively. The acronyms BN and CN
mean biotic niche and climatic niche,
CAI et A l.
or biotic interactions with other species, the regional availability of
suitable niche space or differences in landscape heterogeneity, evo-
lutionary processes or historical events, as well as human impacts
(Boulangeat et al., 2012; Lambdon, 2008; Sillero, 2011; Slayter et al.,
2013; Wandrag et al., 2019).
The North American species F. grandifolia probably represents a
member of the oldest clade (Renner et al., 2016). However, its large
distribution and its relatively low niche breadth may, to a large ex-
tent, represent lower spatial species turnover and environmental
heterogeneity in eastern North America in comparison to Europe
and East Asia. It is well- established that the diversity of angiosperms
in eastern China is larger than in eastern North America (e.g. Qian
et al., 2005). Fagus hayatae has a very disjunct distribution with two
subranges in mainland China and Taiwan Island, and thus, covers
a broad, yet disjunct range of climatic conditions (Hukusima et al.,
2013; Shen, 1992; Shen et al., 2015). Fagus orientalis, although with a
distinctly narrower range size compared to F. grandifolia and F. sy lvat-
ica, covers diverse climatic zones from the Balkan mountain ranges
to the southern Euxinian, Colchic, Eastern Mediterranean and
Hyrcanian regions (Crimea, North Turkey, Caucasus, isolated patches
in southern Turkey and North Iran), in combination with steep el-
evational gradients (Gholizadeh et al., 2020; Kavgaci et al., 2012;
Shen, 1992). For example, in the Hyrcanian area, F. orientalis grows
between around 300 to 2700 m a.s.l., covering a broad range of cli-
matic conditions (from warm and humid to cool and dry) (Gholizadeh
et al., 2020). Similarly, F. sylvatica has a broad ecological amplitude
and a wide range of habitats in Europe (Magri, 2008; Ujházyová
et al., 2016; Willner et al., 2017). The Fagus species in Korea (F. mult-
inervis) and Japan (F. crenata and F. japonica) have narrower biotic and
climatic niche breadth, consistent with these species being limited to
isolated islands, especially for F. multinervis, endemic to Ulleungdo
Island (Hukusima et al., 2013).
The distribution of Fagus was severely influenced by the
Quaternary historical events in the Northern Hemisphere (Huntley
et al., 1989; Liu et al., 2003; Magri, 2008). Following the early
Quaternary, the geographical range of Fagus dramatically shrunk
and shifted southwards during the glacial periods, although the his-
tory of Fagus species during the interglacials before the Holocene
remains unclear (Hukusima et al., 2013; Huntley et al., 1989; Liu
et al., 2003; Magri, 2008; Magri et al., 2006). After the Last Glacial
Maximum, northward or northwestward re- immigration of Fagus
from the southern refugia happened in North America, Europe and
Japan (Huntley et al., 1989; Liu et al., 2003; Magri, 2008), despite
strong dispersal limitations (Saltré et al., 2013). In China, however,
the northward postglacial migration of Fagus was limited by the
monsoon climate with early- season aridity, which restricted the
FIGURE 5 Different characteristics
and their phylogenetic signal for the
10 extant Fagus species, measured by
Blomberg's K. If K is significantly larger
than one, the characteristic is regarded
as phylogenetically conser ved (Blomberg
et al., 2003). Blomberg's K was not
statistically significant (p > 0.05) for any
characteristic. The phylogenetic tree is
based on results provided in Qian and
Jin (2016) and Oh et al. (2016). The size/
colour of the circle represents the scaled
and centred value of the corresponding
characteristic. The acronym MTCM means
minimum temperature of the coldest
CAI et A l.
distribution ranges of the Chinese species to the subtropical region
only (Liu et al., 2003; Shen et al., 2015).
Human activities might have affected the distribution and com-
munity composition of Fagus forests to a certain degree. For ex-
ample, F. sylvatica forests in Europe have been managed for a long
time as beech is an important economic tree for wood production,
especially in northern- central Europe (Magri, 2008). Activities such
as livestock grazing and disturbance of the preceding forests by fire
before Fagus became established have promoted the spread of Fagus
in northern Europe (Bradshaw et al., 2010).
Overall, these idiosyncratic impacts on range dynamics differed
from those factors affecting niche breadth, as witnessed by the ab-
sence of a significant correlation. Our study, with a sample size of
10 species, suffers from low statistical power and does not preclude
finding such a relationship across species within other genera. It
would be, therefore, interesting to benchmark our finding that dif-
ferent factors drive range size and biotic niche width independently
on a larger dataset.
Additionally, the lack of relationship between range size and
niche breadth might also suggest that the prevalent processes of
community assembly differ across Fagus species. In most communi-
ties, both deterministic and stochastic processes are at work simul-
taneously (Stegen & Hurlbert, 2011). Thus, a low taxonomic turnover
(β- diversity), such as in F. grandifolia stands in North America, might
reflect a low impact of stochastic processes, but might also be
brought about by deterministic processes such as strong environ-
mental filtering under homogeneous climatic conditions. In con-
trast, high β- diversity, such as for the Fagus stands in China, might
indicate that stochastic processes dominate (Daniel et al., 2019), re-
sulting from the more pronounced geographical isolation and more
glacial refuge areas in China. However, the same pattern could also
be caused by deterministic processes with different environmental
filtering regimes under heterogeneous climatic conditions.
4.1 | Correlations between niche concepts
The co- occurrence- based biotic niche breadth estimates were uncor-
related with the climatic niche breadth estimates, incongruent with
our second hypothesis (H2). Although positive relationships have been
observed in previous studies (Kambach et al., 2019; Pannek et al.,
2016), it has to be admitted that the two adopted niche concepts dif-
fer greatly in dimensions and spatial scales and thus are not necessarily
correlated (Emery et al., 2012; Pannek et al., 2016). The incongruence
of results based on different indices of realized niche breadth suggests
that these indices carry complementary information.
4.2 | No phylogenetic signal for niche properties
Our results suggest dynamic development of the biotic and the cli-
matic niches, which does not seem to be related to the rooting depth
and phylogenetic distance of the respective clades (Losos, 2008;
Wiens et al., 2010), in contrast with our hypothesis H3. Considering
the lack of a clear phylogenetic signal towards ecological speciali-
zation, we conclude that the complex phylogeographical history of
the genus Fagus does not allow us to find support for the stated
“specialization hypothesis”. In previous studies, both divergent (e.g.
Evans et al., 2009; Graham et al., 2004) and conserved (e.g. Kozak &
Wiens, 2006; Peterson et al., 1999) climatic niches have been related
to speciation processes. For Fagus, factors such as vicariance and
geographical barriers might have resulted in the evolution of biotic
and climatic niche properties. For example, the three species in the
subgenus Engleriana (F. japonica, F. engleriana and F. multinervis) are
closely related and speciated later than the other Chinese species
(Renner et al., 2016), probably as a result of limited gene flow be-
tween separated islands (Japan and Ulleungdo Island in South Korea)
and isolated mountain ranges (Oh et al., 2016). Having evolved from
a common ancestor species, such geographical separation and dif-
ferences in available niche space may result in the development of
different biotic and climatic niches.
Cold tolerance has been regarded as a key trait for the geograph-
ical distribution patterns of trees (Hawkins et al., 2014; Wiens &
Donoghue, 2004). The monthly mean of the minimum daily tempera-
tures (BIO06) has been used to represent the cold tolerance of tree
species for which large scale physiological data are usually hard to ob-
tain (Hawkins et al., 2014). The RF classification analyses revealed that
cold tolerance did not discriminate the species, suggesting it might be
conserved across the whole Fagus- clade, possibly representing an an-
cestral adaptation. Uniform cold tolerance across the genus is consis-
tent with Blomberg's K, revealing the absence of a phylogenetic signal
within the genus. However, testing for conservatism at the genus level
would require a broader taxonomic scope, for example, by including
the whole Fagaceae family. Nevertheless, genus- level conservatism is
suggested by the consistent association of Fagus with mesic temperate
climates, relative to the broader distribution of the family.
5 | CONCLUSIONS
We estimated the biotic and climatic niche breadths of all 10 ex-
tant Fagus species and examined their relationships with range size.
Biotic and climatic niche breadth were uncorrelated with range size
and phylogeny, and also incongruent with each other. Furthermore,
there was no evidence for evolutionary tendencies towards ecologi-
cal specialization in the younger Fagus clades occurring in East Asia.
We conclude that within widespread groups of related species such
as in the Fagus genus, general macroecological patterns such as the
range size– niche breadth relationship might be overridden by dif-
ferent regionally available niche space opportunities, differences in
landscape heterogeneity and Quaternary histories.
We thank all the dat a cont ributo rs and thos e who help ed in the fie ld-
work, as well as M. Sporbert, G. Seidler, Y. H. Feng and H. Zhang for
CAI et A l.
their help in the data processing. This research was supported by the
National Natural Science Foundation of China (no. 31988102), the
National Key Research and Development Program of China (grant no.
2017YFA0605101 and 2017YFC0503906) and Ministry of Science
and Technology of China (grant no. 2015FY210200). We also thank
the support of the Chinese Scholarship Council (CSC) for Q. Cai. Milan
Chytrý was supported by the Czech Science Foundation (project no.
19- 28491X). Jens- Christian Svenning considers this work a contri-
bution to his VILLUM Investigator project “Biodiversity Dynamics
in a Changing World” funded by VILLUM FONDEN (grant 16549)
and his Independent Research Fund Denmark; Natural Sciences
project TREECHANGE (grant 6108- 00078B). Jiri Dolezal was sup-
ported by Ministry of Education, Youth and Sport of the Czech
Republic, program Inter- Excellence (project LTAUSA18007). sPlot is
a strategic project of the German Centre for Integrative Biodiversity
Research (iDiv) Halle- Jena- Leipzig, funded by the German Research
Foundation (DFG FZT 118, 202548816). Additional acknowledge-
ments for the individual datasets composing sPlot are available in
Bruelheide et al. (2019). Open access funding was enabled and or-
ganized by Projekt DEAL. No collecting permits are required for this
Qiong Cai https://orcid.org/0000-0002-7173-1447
Erik Welk https://orcid.org/0000-0002-2685-3795
Francesco M. Sabatini https://orcid.org/0000-0002-7202-7697
Zhiyao Tang https://orcid.org/0000-0003-0154-6403
Fabio Attorre https://orcid.org/0000-0002-7744-2195
Andraž Čarni https://orcid.org/0000-0002-8909-4298
Milan Chytrý https://orcid.org/0000-0002-8122-3075
Süleyman Çoban https://orcid.org/0000-0003-1570-9795
Jürgen Dengler https://orcid.org/0000-0003-3221-660X
Richard Field https://orcid.org/0000-0003-2613-2688
Ute Jandt https://orcid.org/0000-0002-3177-3669
Dirk N. Karger https://orcid.org/0000-0001-7770-6229
Jonathan Lenoir https://orcid.org/0000-0003-0638-9582
Robert K . Peet https://orcid.org/0000-0003-2823-6587
Remigiusz Pielech https://orcid.org/0000-0001-8879-3305
Michele De Sanctis https://orcid.org/0000-0002-7280-6199
Franziska Schrodt https://orcid.org/0000-0001-9053-8872
Jens- Christian Svenning https://orcid.org/0000-0002-3415-0862
Cindy Q. Tang https://orcid.org/0000-0003-3789-6771
Ioannis Tsiripidis https://orcid.org/0000-0001-9373-676X
Wolfgang Willner https://orcid.org/0000-0003-1591-8386
Helge Bruelheide https://orcid.org/0000-0003-3135-0356
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Qiong Cai is interested in plant community ecology, espe-
cially that of the genus Fagus. This work is the result of a co-
operation project during her one- year visit at the Institute for
Biology, Department of Geobotany, Martin- Luther- University
Author contributions: H.B. and E.W. conceived the ideas; all the
authors collected the data; Q.C., H.B., E.W. analysed the data;
and Q.C., H.B., E.W. and J.Y.F. led the writing with assistance
from the other authors.
Additional supporting information may be found online in the
Supporting Information section.
How to cite this article: Cai Q, Welk E, Ji C, et al. The
relationship between niche breadth and range size of beech
(Fagus) species worldwide. J Biogeogr. 2021;00:1–14. ht t p s : //